Probing the Histamine H1 Receptor Binding Site to Explore Ligand Binding Kinetics
Abstract
High Resolution Image Download MS PowerPoint Slide Analysis of structure-kinetic relationships (SKR) can contribute to an improved understanding of receptor–ligand interactions. Here, fragment 1 (4-(2-benzylphenoxy)-1-methylpiperidine) was used in different fragment growing approaches to mimic the putative binding mode of the long residence time (RT) ligands olopatadine, acrivastine, and levocetirizine at the histamine H 1 receptor (H 1 R). SKR analyses reveal that introduction of a carboxylic acid moiety can increase RT at H 1 R up to 11-fold. Ligand efficiency (LE) decreases upon the introduction of the negatively charged group, whereas kinetic efficiency (KE) increases up to 8.5-fold. The olopatadine/acrivastine mimics give up to 15-fold differences in the RT, while the levocetirizine mimics afford similar RTs with only a 3-fold difference. Therefore, the levocetirizine mimics are less sensitive to structural changes. This study illustrates that for H 1 R, there are several ways to increase RT but the different strategies differ significantly in SKR.
Read the paper
Related studies
- Artificial Intelligence in Medicine: Cross-Sectional Study Among Medical Students on Application, Education, and Ethical Aspects
- Information quality of videos related to esophageal cancer on tiktok, kwai, and bilibili: a cross-sectional study
- The quality and reliability of short videos about hypertension on TikTok: a cross-sectional study
- Quality and reliability evaluation of pancreatic cancer-related video content on social short video platforms: a cross-sectional study
- Quality and reliability of pediatric pneumonia related short videos on mainstream platforms: cross-sectional study
- Association between metabolic score for insulin resistance (METS-IR) and hypertension: a cross-sectional study based on NHANES 2007–2018
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.